A malignant tumor patient cancer pain home nursing monitoring system

Abstract

This invention relates to the field of medical and health information technology and discloses a home-based pain monitoring system for malignant tumor patients. The invention collects various data related to home care of malignant tumor patients, forming pain datasets, medication datasets, and vital sign datasets. Based on these three datasets, pain risk indices, medication risk indices, and vital sign risk indices are obtained. These are then weighted and summed to obtain a comprehensive risk index. Effective correlation and collaborative analysis of multi-dimensional data improve the accuracy of the comprehensive risk index. The system determines whether to issue an alert based on the comprehensive risk index. If the comprehensive risk index reaches a threshold, three different levels of alerts (red, orange, and yellow) are issued and sent to both the patient-side interaction module and the medical staff-side interaction module. Upon receiving the alert, medical staff immediately review the patient's current condition report, analyze it, and receive timely improvement suggestions to help the patient improve their current condition, thus improving the efficiency of home care.

Description

Technical Field

[0001] This invention relates to the field of medical and health information technology, specifically to a home care monitoring system for cancer pain in patients with malignant tumors. Background Technology

[0002] Cancer pain is one of the most common symptoms affecting the quality of life of patients with malignant tumors, with approximately 60% to 80% of patients with advanced-stage cancer experiencing moderate to severe pain. Effective pain management is central to palliative care, but current mainstream cancer pain management models have significant shortcomings, leading to a large number of patients facing poor pain control at home.

[0003] Traditional cancer pain management relies heavily on regular outpatient visits (usually every 1-2 weeks or longer). In the consultation room, doctors adjust treatment based on the patient's verbal recollection and description of past pain. This approach suffers from significant time lag, subjectivity, and information distortion. Sudden, severe pain at home cannot receive timely professional guidance, and medication adherence, standardization, and adverse reactions remain unmonitored. Because healthcare professionals lack access to continuous, objective, and dynamic data, their treatment decisions are often based on incomplete information, leading to delayed adjustments to analgesia regimens and compromised effectiveness.

[0004] With the development of mobile health technology, some pain management applications and simple remote reporting tools have emerged. However, most existing solutions are functionally limited and isolated. For example, most existing solutions only record patients' self-reported subjective pain scores, lacking effective correlation and fusion analysis with objective physiological signs (such as sleep and activity levels), actual medication behavior, and other multi-dimensional data. Furthermore, existing solutions employ static assessment methods, lacking dynamic risk assessment and early warning capabilities based on multi-source data, and are unable to identify risk trends before pain becomes uncontrollable. Simultaneously, they fail to establish a closed-loop collaborative workflow connecting patients and healthcare professionals, resulting in a disconnect between patient-side data reporting and healthcare intervention guidance. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a home-based nursing monitoring system for cancer pain in patients with malignant tumors. This system features the ability to collect multidimensional data on patients' home care, conduct multi-angle assessment and analysis, and achieve early risk warning through intelligent algorithms. It constructs a home-based nursing health system that enables efficient collaboration between the patient and medical care ends, thereby improving the patient's quality of life and solving the aforementioned technical problems.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a home care monitoring system for cancer pain in patients with malignant tumors, comprising a patient-side intelligent interaction module, a cloud data monitoring and analysis module, an intelligent early warning module, and a medical staff-side interaction module; The patient-side interaction module is used to acquire various data of the patient's home care, which are respectively composed of pain dataset, medication dataset and vital signs dataset. The patient-side interaction module is also used to receive early warnings. The cloud data monitoring and analysis module includes a pain assessment unit, a medication assessment unit, and a vital sign assessment unit. The pain assessment unit obtains a pain risk index based on a pain dataset, the medication assessment unit obtains a medication risk index based on a medication dataset, and the vital sign assessment unit obtains a vital sign risk index based on a vital sign dataset. The cloud data monitoring and analysis module weights and sums the pain risk index, the medication risk index, and the vital sign risk index to obtain a comprehensive risk index. The intelligent early warning module determines whether to issue an early warning to the patient-side interaction module and the medical staff-side interaction module based on a comprehensive risk index. The medical staff interaction module is used to generate a patient's condition report after receiving an alert.

[0007] As a preferred embodiment of the present invention, the expression of the pain dataset is: ,in, Indicates the patient's home care Daily pain data, Indicates the patient's home care The pain data includes the number of pain episodes and the pain score corresponding to each pain episode, which is obtained based on the NRS numerical rating scale.

[0008] As a preferred embodiment of the present invention, the expression of the medication dataset is: ,in, Indicates the patient's home care Daily medication data, Indicates the patient's home care Daily medication data, including the number of times the patient takes medication on time, the number of times medication should be taken, and the number of times emergency medication is used.

[0009] As a preferred embodiment of the present invention, the expression for the vital signs dataset is: ,in, Indicates the patient's home care Daily vital signs data, Indicates the patient's home care Daily vital signs data, including the patient's sleep duration and number of steps taken.

[0010] As a preferred embodiment of the present invention, the expression for the pain risk index is as follows: ; in, Indicates the patient's home care Daily pain risk index; Indicates the patient's home care The maximum daily pain score; This represents the maximum value set for the pain score, used to normalize the patient's actual pain score; This indicates taking the minimum value; Indicates the patient's home care The number of daily pain episodes; This indicates the set threshold for the number of pain attacks; and Indicates the weighting coefficient. .

[0011] As a preferred embodiment of the present invention, the expression for the medication risk index is as follows: ; in, Indicates the patient's home care Daily medication risk index; Indicates the patient's home care The frequency of daily medication administration; Indicates the patient's home care The number of times medication should be taken per day; This indicates taking the minimum value; Indicates the patient's home care The number of times daily emergency medication is used; This indicates the set threshold for the number of times emergency medication can be used; and Indicates the weighting coefficient. .

[0012] As a preferred embodiment of the present invention, the expression for the vital sign risk index is as follows: ; in, Indicates the patient's home care Daily vital signs risk index; Indicates the patient's home care Daily sleep duration; Indicates the patient's home care Daily activity steps; This indicates that the summation calculation was performed on the patient's home care over the past 7 days; This indicates taking the maximum value; and Indicates the weighting coefficient. .

[0013] As a preferred embodiment of the present invention, the expression for the comprehensive risk index is as follows: ; in, Indicates the patient's home care The overall risk index for the day; Indicates the patient's home care Daily pain risk index; Indicates the patient's home care Daily medication risk index; Indicates the patient's home care Daily vital signs risk index; , and These represent the weighting coefficients, .

[0014] As a preferred embodiment of the present invention, the intelligent early warning module determines whether to issue an early warning to the patient-side interaction module and the medical staff-side interaction module based on a comprehensive risk index, specifically as follows: When the comprehensive risk index A red alert is issued when the second threshold is greater than or equal to the first threshold; a red alert is issued when the second threshold is less than or equal to the comprehensive risk index. When the risk level is less than the first threshold, an orange alert is issued; when the third threshold is less than or equal to the comprehensive risk index... A yellow alert is issued when the comprehensive risk index is below the second threshold; If the threshold is less than the third threshold, no warning will be issued.

[0015] As a preferred embodiment of the present invention, the process of generating the patient's medical report includes the following steps: Step A1: After receiving the alert, the medical staff interaction module retrieves the patient's complete historical home care data; Step A2: Analyze the patient's home care, as follows: If the patient's proportion of dangerous days If the patient's home care is not effective, the percentage of critical days is higher than the set threshold. The set threshold indicates that the patient's home care has met the required standards; Step A3: Generate the patient's medical report; The formula for the proportion of critical days for the patient is: ,in, This indicates the percentage of patients in critical condition as of that date; This indicates the number of days an alert was issued during the patient's home care process; This indicates the day in the patient's home care process.

[0016] Compared with the prior art, the present invention provides a home care monitoring system for cancer pain in patients with malignant tumors, which has the following beneficial effects: This invention collects various data from home care of malignant tumor patients, forming pain datasets, medication datasets, and vital sign datasets. Based on these three datasets, pain risk indices, medication risk indices, and vital sign risk indices are obtained. These are then weighted and summed to obtain a comprehensive risk index. Effective correlation and collaborative analysis of multi-dimensional data improve the accuracy of the comprehensive risk index. Based on the comprehensive risk index, a warning is issued. If the comprehensive risk index reaches a threshold, a warning of three different levels (red, orange, and yellow) is issued and sent to both the patient-side interaction module and the medical staff-side interaction module. Upon receiving the warning, medical staff can immediately view the patient's current condition report, analyze it, and obtain timely improvement suggestions to help the patient improve their current condition, thus improving the efficiency of home care. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the system framework of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see Figure 1 A home care monitoring system for cancer pain in patients with malignant tumors includes: a patient-side intelligent interaction module, a cloud data monitoring and analysis module, an intelligent early warning module, and a medical staff-side interaction module; The patient-side interaction module is used to acquire various data on patients’ home care, which are respectively composed of pain dataset, medication dataset and vital signs dataset. The patient-side interaction module is also used to receive alerts. The expression for the pain dataset is: ,in, Indicates the patient's home care Daily pain data, Indicates the patient's home care Daily pain data includes the number of pain episodes and the pain score corresponding to each pain episode. The pain score is obtained based on the NRS numerical rating scale, which is a widely used pain assessment method in clinical practice. The expression for the medication dataset is: ,in, Indicates the patient's home care Daily medication data, Indicates the patient's home care Daily medication data includes the number of times a patient takes medication on time, the number of times a medication should be taken, and the number of times emergency medication is used. The expression for the vital signs dataset is: ,in, Indicates the patient's home care Daily vital signs data, Indicates the patient's home care Daily vital signs data, including the patient's sleep duration and number of steps taken; The cloud data monitoring and analysis module includes a pain assessment unit, a medication assessment unit, and a vital sign assessment unit. The pain assessment unit obtains a pain risk index based on the pain dataset, the medication assessment unit obtains a medication risk index based on the medication dataset, and the vital sign assessment unit obtains a vital sign risk index based on the vital sign dataset. The cloud data monitoring and analysis module weights and sums the pain risk index, the medication risk index, and the vital sign risk index to obtain a comprehensive risk index. The expression for the pain risk index is as follows: ; in, Indicates the patient's home care Daily pain risk index; Indicates the patient's home care The maximum daily pain score; This represents the maximum value set for the pain score, used to normalize the patient's actual pain score; This indicates taking the minimum value; Indicates the patient's home care The number of daily pain episodes; This indicates the set threshold for the number of pain attacks; and Indicates the weighting coefficient. ; This reflects the abnormal degree of pain experienced by patients with malignant tumors on that day; the more intense the pain, the higher the severity. The higher the value, the more frequent the pain attacks. The higher the value, the less optimistic the patient's condition is on that day. The formula uses... The function is normalized so that The maximum value does not exceed 1; The expression for the medication risk index is as follows: ; in, Indicates the patient's home care Daily pain risk index; Indicates the patient's home care The maximum daily pain score; This represents the maximum value set for the pain score, used to normalize the patient's actual pain score; This indicates taking the minimum value; Indicates the patient's home care The number of daily pain episodes; This indicates the set threshold for the number of pain attacks; and Indicates the weighting coefficient. ; This reflects the abnormal degree of pain experienced by patients with malignant tumors on that day; the more intense the pain, the higher the severity. The higher the value, the more frequent the pain attacks. The higher the value, the less optimistic the patient's condition is on that day. The formula uses... The function is normalized so that The maximum value does not exceed 1; The expression for the medication risk index is as follows: ; The expression for the comprehensive risk index is as follows:

[0020] in, Indicates the patient's home care The overall risk index for the day; Indicates the patient's home care Daily pain risk index; Indicates the patient's home care Daily medication risk index; Indicates the patient's home care Daily vital signs risk index; , and These represent the weighting coefficients, ; The intelligent early warning module determines whether to issue an early warning to both the patient-side and medical staff-side interaction modules based on a comprehensive risk index. Specifically: When the comprehensive risk index A red alert is issued when the second threshold is greater than or equal to the first threshold; a red alert is issued when the second threshold is less than or equal to the comprehensive risk index. When the risk level is less than the first threshold, an orange alert is issued; when the third threshold is less than or equal to the comprehensive risk index... A yellow alert is issued when the comprehensive risk index is below the second threshold; If the threshold is less than the third threshold, no warning will be issued. The healthcare worker interaction module is used to generate a patient's condition report after receiving an alert. The process of generating the condition report includes the following steps: Step A1: After receiving the alert, the medical staff interaction module retrieves the patient's complete historical home care data; The expression for the comprehensive risk index is as follows: ; in, Indicates the patient's home care The overall risk index for the day; Indicates the patient's home care Daily pain risk index; Indicates the patient's home care Daily medication risk index; Indicates the patient's home care Daily vital signs risk index; , and These represent the weighting coefficients, ; The intelligent early warning module determines whether to issue an early warning to both the patient-side and medical staff-side interaction modules based on a comprehensive risk index. Specifically: When the comprehensive risk index A red alert is issued when the second threshold is greater than or equal to the first threshold; a red alert is issued when the second threshold is less than or equal to the comprehensive risk index. When the risk level is less than the first threshold, an orange alert is issued; when the third threshold is less than or equal to the comprehensive risk index... A yellow alert is issued when the comprehensive risk index is below the second threshold; If the threshold is less than the third threshold, no warning will be issued. The healthcare worker interaction module is used to generate a patient's condition report after receiving an alert. The process of generating the condition report includes the following steps: Step A1: After receiving the alert, the medical staff interaction module retrieves the patient's complete historical home care data; Step A2: Analyze the patient's home care, as follows: If the patient's proportion of dangerous days If the patient's home care is not effective, the percentage of critical days is higher than the set threshold. The set threshold indicates that the patient's home care has met the required standards; The formula for the proportion of critical days for patients is: ,in, This indicates the percentage of patients in critical condition as of that date; This indicates the number of days a warning was issued during the patient's home treatment process; This indicates which day corresponds to the patient's home treatment process; Step A3: Generate the patient's condition report. Medical staff can use the patient's condition report to assess and obtain suggestions for improving the patient's home care.

[0021] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A home-based cancer pain monitoring system for patients with malignant tumors, characterized in that: It includes a patient-side intelligent interaction module, a cloud data monitoring and analysis module, an intelligent early warning module, and a medical staff-side interaction module; The patient-side interaction module is used to acquire various data of the patient's home care, which are respectively composed of pain dataset, medication dataset and vital signs dataset. The patient-side interaction module is also used to receive early warnings. The cloud data monitoring and analysis module includes a pain assessment unit, a medication assessment unit, and a vital sign assessment unit. The pain assessment unit obtains a pain risk index based on a pain dataset, the medication assessment unit obtains a medication risk index based on a medication dataset, and the vital sign assessment unit obtains a vital sign risk index based on a vital sign dataset. The cloud data monitoring and analysis module weights and sums the pain risk index, the medication risk index, and the vital sign risk index to obtain a comprehensive risk index. The intelligent early warning module determines whether to issue an early warning to the patient-side interaction module and the medical staff-side interaction module based on a comprehensive risk index. The medical staff interaction module is used to generate a patient's condition report after receiving an alert.

2. The home-based cancer pain monitoring system for patients with malignant tumors according to claim 1, characterized in that: The expression for the pain dataset is: ,in, Indicates the patient's home care Daily pain data, Indicates the patient's home care The pain data includes the number of pain episodes and the pain score corresponding to each pain episode, which is obtained based on the NRS numerical rating scale.

3. The home-based nursing monitoring system for cancer pain in patients with malignant tumors according to claim 2, characterized in that: The expression for the medication dataset is: ,in, Indicates the patient's home care Daily medication data, Indicates the patient's home care Daily medication data, including the number of times the patient takes medication on time, the number of times medication should be taken, and the number of times emergency medication is used.

4. A home-based cancer pain monitoring system for patients with malignant tumors according to claim 3, characterized in that: The expression for the vital signs dataset is: ,in, Indicates the patient's home care Daily vital signs data, Indicates the patient's home care Daily vital signs data, including the patient's sleep duration and number of steps taken.

5. A home-based cancer pain monitoring system for patients with malignant tumors according to claim 4, characterized in that: The expression for the pain risk index is as follows: ； in, Indicates the patient's home care Daily pain risk index; Indicates the patient's home care The maximum daily pain score; This represents the maximum value set for the pain score, used to normalize the patient's actual pain score; This indicates taking the minimum value; Indicates the patient's home care The number of daily pain episodes; This indicates the set threshold for the number of pain attacks; and Indicates the weighting coefficient. .

6. A home-based cancer pain monitoring system for patients with malignant tumors according to claim 5, characterized in that: The expression for the medication risk index is as follows: ； in, Indicates the patient's home care Daily medication risk index; Indicates the patient's home care The frequency of daily medication administration; Indicates the patient's home care The number of times medication should be taken per day; This indicates taking the minimum value; Indicates the patient's home care The number of times daily emergency medication is used; This indicates the set threshold for the number of times emergency medication can be used; and Indicates the weighting coefficient. .

7. A home-based cancer pain monitoring system for patients with malignant tumors according to claim 6, characterized in that: The expression for the vital sign risk index is as follows: ； in, Indicates the patient's home care Daily vital signs risk index; Indicates the patient's home care Daily sleep duration; Indicates the patient's home care Daily activity steps; This indicates that the summation calculation was performed on the patient's home care over the past 7 days; This indicates taking the maximum value; and Indicates the weighting coefficient. .

8. A home-based cancer pain monitoring system for patients with malignant tumors according to claim 7, characterized in that: The expression for the comprehensive risk index is as follows: ； in, Indicates the patient's home care The overall risk index for the day; Indicates the patient's home care Daily pain risk index; Indicates the patient's home care Daily medication risk index; Indicates the patient's home care Daily vital signs risk index; , and These represent the weighting coefficients, .

9. A home-based cancer pain monitoring system for patients with malignant tumors according to claim 8, characterized in that: The intelligent early warning module determines whether to issue an early warning to the patient-side interaction module and the medical staff-side interaction module based on a comprehensive risk index. Specifically: When the comprehensive risk index A red alert is issued when the second threshold is greater than or equal to the first threshold; a red alert is issued when the second threshold is less than or equal to the comprehensive risk index. When the risk level is less than the first threshold, an orange alert is issued; when the third threshold is less than or equal to the comprehensive risk index... A yellow alert is issued when the comprehensive risk index is below the second threshold; If the threshold is less than the third threshold, no warning will be issued.

10. A home-based cancer pain monitoring system for patients with malignant tumors according to claim 9, characterized in that: The process of generating the patient's medical report includes the following steps: Step A1: After receiving the alert, the medical staff interaction module retrieves the patient's complete historical home care data; Step A2: Analyze the patient's home care, as follows: If the patient's proportion of dangerous days If the patient's home care is not effective, the percentage of critical days is higher than the set threshold. The set threshold indicates that the patient's home care has met the required standards; Step A3: Generate the patient's medical report; The formula for the proportion of critical days for the patient is: ,in, This indicates the percentage of patients in critical condition as of that date; This indicates the number of days an alert was issued during the patient's home care process; This indicates the day in the patient's home care process.

Images